For service and diagnostic purposes, machines are sometimes equipped with sensors for measuring operating parameters such as engine RPM, oil pressure, water temperature, boost pressure, oil contamination, electric motor current, hydraulic pressure, system voltage, exhaust manifold temperature and the like. In some cases, storage devices are provided to compile a database for later evaluation of machine performance and to aid in diagnosis. Service personnel examine the accrued data to determine the cause(s) of any failure or to aid in diagnosis. Similarly, service personnel can evaluate the stored data to predict future failures and to correct any problems before an actual failure occurs. Such diagnosis and failure prediction are particularly pertinent to over-the-highway trucks and large work machines such as off-highway mining trucks, hydraulic excavators, track-type tractors, wheel loaders, and the like. Stationary machines such as large stationary engines can also benefit from accurate component diagnosis and failure prediction. These machines represent large capital investments and are capable of substantial productivity when operating properly. It is therefore important to fix or replace degraded components and to predict failures so minor problems can be repaired before they lead to catastrophic failures, and so servicing can be scheduled during periods in which productivity will be least affected.
Systems used in the past often acquire and store data from the machine sensors during different machine operating conditions. For example, some data is acquired while the engine is idling while other data is acquired while the engine is under full load. This poses a problem for service personnel to compare data acquired under such different circumstances and to observe meaningful trends in the sensed parameters.
It is sometimes advantageous to accumulate parameters only when the machine is in a particular operating condition. This type of information is predominantly used during performance evaluation but may also be used in failure diagnosis and prognosis.
To further aid in diagnostics, it is beneficial to package information in such a way that the analysis is simplified as much as possible.
Where a machine includes similar or identical components or systems loaded in parallel during operation, comparisons are sometimes made between two or more of these like-loaded components to diagnose problems or predict failure. One known method is the "hands-on" approach, in which the machine operator or maintenance personnel physically look, listen or feel for differences between the two components during operation. For example, machine operators have been known to feel for temperature differences between cylinder banks or ports looking for causes of poor fuel mileage.
Another known technique for comparing similarly-loaded components is the "drop-out test," in which individual components are selectively turned off to determine which dropped-out component has the least effect on engine or system output.
Other known methods for assessing the comparative performance of various components include the use of chassis dynamometers for measuring the difference between vehicle wheel or drive shaft performance, exhaust pyrometer and cylinder port gages to indicate differences in exhaust manifold or cylinder temperatures, and other non-historical comparison methods and devices. Drawbacks of known component-comparing methods and devices include the subjective nature of many tests; the fact that many tests cannot be performed under actual operating conditions; the lack of historical component-to-component comparison data accumulated during periods of vehicle operation; and difficulty in usefully comparing the data from multiple components such that degradation or failure of one or more of them can be readily determined.